论文标题
通过触觉感知接触表面估计
Contact Surface Estimation via Haptic Perception
论文作者
论文摘要
腿部系统需要优化接触力以维持联系。为此，控制器需要了解表面几何形状以及地形的湿滑。我们可以使用视觉系统来实现地形，但是视觉系统在恶劣的天气中的准确性降低了，如果地形被水或草覆盖，它就无法可视化地形。同样，摩擦程度不能直接可视化。在本文中，我们提出了一种在线方法，以通过触觉探索估算表面信息。我们还引入了一个概率标准，以衡量估计的质量。该方法在模拟和真实机器人平台上均已验证。
Legged systems need to optimize contact force in order to maintain contacts. For this, the controller needs to have the knowledge of the surface geometry and how slippery the terrain is. We can use a vision system to realize the terrain, but the accuracy of the vision system degrades in harsh weather, and it cannot visualize the terrain if it is covered with water or grass. Also, the degree of friction cannot be directly visualized. In this paper, we propose an online method to estimate the surface information via haptic exploration. We also introduce a probabilistic criterion to measure the quality of the estimation. The method is validated on both simulation and a real robot platform.
